Information
----Curriculum Vitae
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Research
----Publications
----Talks
 
Background
----Grants & Awards
----Brief Biosketch
 
Machine Learning at Toronto
learning.cs.toronto.edu
 
My Home Page
www.cs.toronto.edu/~rsalakhu
 
[Image]

 

Ruslan Salakhutdinov
PhD Student
Department of Computer Science
University of Toronto
6 King's College Rd.
Toronto, Ontario, Canada
M5S 3G4
Email: rsalakhu (at) cs (dot) toronto (dot) edu
Office: Pratt 265A

I am a PhD student at University of Toronto, where I work with Geoffrey Hinton and Sam Roweis.
  • Quick link to my research papers

    Reducing the Dimensionality of Data with Neural Networks.
    Geoffrey E. Hinton and Ruslan R. Salakhutdinov
    Science, 28 July 2006:
    Vol. 313. no. 5786, pp. 504 - 507
    [bibtex] [pdf][ Science Online]
    Supporting Online Material [pdf, Science Online]
    Matlab Code is available here

    Recent Papers
    Ruslan Salakhutdinov
    Learning and Evaluating Boltzmann Machines
    Technical Report UTML TR 2008-002, Dept. of Computer Science, University of Toronto
    [bibtex] [ps.gz][ pdf]
    This paper introduces a new Boltzmann machine learning algorithm that combines variational techniques and MCMC.

  • Ruslan Salakhutdinov and Iain Murray
    On the Quantitative Analysis of Deep Belief Networks
    To appear in 25th International Conference on Machine Learning (ICML-2008)
    [bibtex] [ps.gz][ pdf] [code]

  • Ruslan Salakhutdinov and Andriy Mnih
    Bayesian Probabilistic Matrix Factorization using MCMC
    To appear in 25th International Conference on Machine Learning (ICML-2008)
    [bibtex] [ps.gz][ pdf]


    Notes

  • Iain Murray and Ruslan Salakhutdinov
    Notes on the KL-divergence between a Markov chain and its equilibrium distribution
    [pdf]


    Recent Talks

  • I was co-organizing Deep Learning Workshop: Foundations and Future Directions, NIPS 2007.

  • Here is the talk that I gave at the workshop on Numerical Tools and Fast Algorithms for Massive Data Mining, Search Engines and Applications.
    Deep Belief Networks with applications to Fast Document Retrieval (ps.gz, pdf).
    IPAM, UCLA, Oct 2007.

  • Deep Belief Nets (ps.gz, pdf).
    Snowbird workshop, March 2007.
    Demo and explanation of Digits and Faces.

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    Ruslan Salakhutdinov, Artificial Intelligence Group, Toronto Computer Science || www.cs.toronto.edu/~rsalakhu